Thesis Details

Využití strojového učení pro zvýšení robustnosti určení pozice v bezdrátovém pozičním systému

Master's Thesis Student: Matuš Adam Academic Year: 2021/2022 Supervisor: Šimek Václav, Ing.
English title
Using Machine Learning for Improvement of Location Estimation in Wireless Positioning System
Language
Czech
Abstract

This thesis describes the Sewio platform and the communication techniques of the ultra-wideband technology standard, which the platform uses to determine the position of objects. The technology is based on measuring signal arrival time intervals and multilateration using time differences. The platform generates and stores historical data from past positioning of objects. The dataset consists of sequences of position data which, in addition to the monitored environment, contain relevant signal parameters of wireless communication. A system of machine learning techniques based on Gaussian models and linear regression was implemented to classify and predict real-time position data with the goal of improving position estimation stability and robustness. The system functions as a downstream component, which accepts RTLS position data and outputs improved position estimates. The evaluation results show that the implemented system can successfully improve position stability and robustness.

Keywords

Machine learning, real-time location system (RTLS), ultra-wideband (UWB), indoor positioning, classification, prediction

Department
Degree Programme
Files
Status
defended, grade C
Date
20 June 2022
Reviewer
Committee
Zbořil František V., doc. Ing., CSc. (DITS FIT BUT), předseda
Bidlo Michal, Ing., Ph.D. (DCSY FIT BUT), člen
Janoušek Vladimír, doc. Ing., Ph.D. (DITS FIT BUT), člen
Kanich Ondřej, Ing., Ph.D. (DITS FIT BUT), člen
Peringer Petr, Dr. Ing. (DITS FIT BUT), člen
Smrž Pavel, doc. RNDr., Ph.D. (DCGM FIT BUT), člen
Citation
MATUŠ, Adam. Využití strojového učení pro zvýšení robustnosti určení pozice v bezdrátovém pozičním systému. Brno, 2022. Master's Thesis. Brno University of Technology, Faculty of Information Technology. 2022-06-20. Supervised by Šimek Václav. Available from: https://www.fit.vut.cz/study/thesis/24508/
BibTeX
@mastersthesis{FITMT24508,
    author = "Adam Matu\v{s}",
    type = "Master's thesis",
    title = "Vyu\v{z}it\'{i} strojov\'{e}ho u\v{c}en\'{i} pro zv\'{y}\v{s}en\'{i} robustnosti ur\v{c}en\'{i} pozice v bezdr\'{a}tov\'{e}m pozi\v{c}n\'{i}m syst\'{e}mu",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2022,
    location = "Brno, CZ",
    language = "czech",
    url = "https://www.fit.vut.cz/study/thesis/24508/"
}
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